网上药店“一单多品”订单的协同配送优化方法

线上线下融合的商业模式是当前电子商务乃至网上药店新的经营模式和发展方向.由于药品是特殊商品，其物流配送的"安全性"和"时间紧迫性"等要求远远高于一般日用品.网上药店和实体药店融合并协同运作，这是解决药品电子商务物流配送难题的有效手段.不同药品由于存储条件不同，必须分类存储，由此产生了"一地多仓"的布局.实体药店作前置仓的履行模式能够满足药品订单的时效性，但药品种类繁多且实体药店库存有限，部分"一单多品"订单需要多个实体药店协作才能完成订单.在"一地多仓"以及"一单多品"的网上药店背景下，本文针对带时间窗的药品订单的多主体协同配送问题，研究订单拆分、子订单分配以及订单主体之间的联合配送决策，构建目标函数为订单配送成本最小化的非线性规划模型.然后，设计定性的控制规则缩减解空间，嵌套C-W节约算法构造改进粒子群算法，能够有效求解本文的多个子问题联合决策的复杂问题.最后通过算例实验，验证了模型与算法的科学性和有效性，并且在一定程度上论证了药品协同配送模式的可行性和实用性，为网上药店实践提供一定的思路和启示.

Collaborative delivery optimization method of online pharmacy with multi-item order

The online merge offline is the new business mode and development direction of current e-commerce especially online pharmacies. Since the drug is the special commodity, the requirements on "safety" and "time urgency" in drug logistics and distribution are much higher than common commodities. The integration and collaboration of online pharmacies and physical pharmacies is an effective means to solve the difficulties in logistics and distribution of drug e-commerce. Different drugs must be classified and stored separately due to different storage requirements, which resulting in the layout of "multi-warehouse in one metropolitan area". The fulfillment mode that takes physical pharmacies as pre-warehouse can satisfy the timeliness of the drug orders. But there are many kinds of drugs and the physical pharmacy space is limited, so some "multi-item orders" need to be completed by multiple physical pharmacies. In the context of online pharmacies with "multi-warehouse in one metropolitan area" and "multi-item order", this paper studies the issue of order splitting, sub-order allocation and joint distribution among order entities for multi-agent collaborative delivery of drug orders with time windows. A non-linear programming model is constructed, whose objective function is to minimize the cost of order delivery. Then the qualitative control rules are designed to reduce solution space. And the heuristic algorithm that the C-W saving algorithm is nested in the improved particle swarm optimization (PSO) is constructed, which can effectively solve the complex problem of multiple sub-problems' joint decision-making in this paper. Finally, the scientificity and validity of the model and algorithm are verified by the numerical experiment. Meanwhile, the results demonstrate the feasibility and practicability of drug collaborative delivery to a certain extent, and these provide some ideas and inspiration for the practice of online pharmacy.